In general, current cellular communications systems allow for cellular devices to connect to high-speed data networks using radio waves as the transmission medium. For example, Universal Mobile Telecommunications Systems (UMTS) can provide broadband applications, internet access, telephone access services, televisions service access and/or mobile telephone services.
Communication over UMTS requires transmission over a radio spectrum, which is a medium that is shared between multiple technologies. In some instances, these technologies can be interfering. Standards were developed to, for example, ensure interoperability between equipment from multiple vendors and aims to ensure that the allocated spectrum is used efficiently.
One such widely adopted standard is the 3rd Generation Partnership Project (3GPP) standard. The 3GPP standard has had many revisions, including an evolution into the Long-Term Evolution (LTE) standards. The LTE standards also continue to evolve, such that there are multiple releases, one of which is the LTE standards Release 11 (e.g., Rel-11).
In cellular communication, a user equipment (UE), for example, a mobile handset, can be required to measure base station power and signal quality of neighboring base stations and report those measurements to its serving base station. These measurements can be used by networks to, for example, manage cell handover. These measurements can have a direct impact on the overall network capacity.
In LTE the UE can report two parameters: Reference Signal Received Power (RSRP) and Reference Signal Received Quality (RSRQ). These two parameters can be measured using sequence of pilots that are typically unique per cell. The sequence of pilots is typically known as Cell specific Reference Signal (CRS).
Currently, cellular communications systems environments are dense and cell coverage areas are small, as demand for cellular service grows. Denser cellular environments and smaller cells can reduce the accuracy of measuring RSRP and RSRQ, due to, for example increased interference.
Rel-11 of the LTE standards attempts to improve accuracy of measuring RSRP and RSRQ by requiring interference cancellation of CRS from neighboring cells. One current method for interference cancellation of CRS from neighboring cells includes performing a joint estimation of a target cell's (e.g., the cell to be measured) channel response and an interfering cell's channel response, followed by averaging of the target cell channel energy over a measurement period.
One difficulty with this current method is that it can require a high computational power, due to, for example, filter coefficients used to estimate the channel response being dependent on a cross correlation of the target cell's and interfering cell's CRS patterns. The cross correlation can vary between orthogonal frequency-division multiplexing (OFDM) symbols and sub-frames, resulting in a matrix inversion calculation for every OFDM symbol. The increase in computation power necessary for joint estimation scan cause a UE to completely fail to function, cause a slowdown of other functions by the UE, the UE to need a bigger processing chip and/or quicker power loss.
Another current method of interference cancellation is serial interference cancellation. In serial cancellation a dominant interfering cell channel is estimated, reconstructed, and subtracted from a received signal. After the serial interference cancellation, the RSRP of the target cell can be estimated. One difficulty with serial interference cancellation is that it can lead to an underestimation of the RSRP of the target cell due to, for example, failure of the dominant interfering cell channel estimation to account for a contribution of the target cell in the received communication signal. Without accounting for the target cell, some of the energy of the target cell (e.g., the projection of the serving cell on the interference cell) is attributed to the interfering cell. Lack of accounting for the target cell can result in a power of the interfering cell being overestimated (e.g., due to a bias primarily caused by the contribution of the target cell in the interfering cell channel estimation), and thus underestimation of the target cell.
Therefore, it is desirable to perform interference cancellation when estimating RSRP with a low computation power. It is also desirable to account for interference cancellation bias in the RSRP estimation.